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We present a generalized version of SnowTran-3D (version 2.0), that simulates wind-related snow distributions over the range of topographic and climatic environments found globally. This version includes three primary enhancements to the original Liston and Sturm (1998) model: (1) an improved wind sub-model, (2) a two-layer sub-model describing the spatial and temporal evolution of friction velocity that must be exceeded to transport snow (the threshold friction velocity) and (3) implementation of a three-dimensional, equilibrium-drift profile sub-model that forces SnowTran-3D snow accumulations to duplicate observed drift profiles. These three sub-models allow SnowTran-3D to simulate snow-transport processes in variable topography and different snow climates. In addition, SnowTran-3D has been coupled to a high-resolution, spatially distributed meteorological model (MicroMet) to provide more realistic atmospheric forcing data. MicroMet distributes data (precipitation, wind speed and direction, air temperature and relative humidity) obtained from meteorological stations and/or atmospheric models located within or near the simulation domain. SnowTran-3D has also been coupled to a spatially distributed energy- and mass-balance snow-evolution modeling system (SnowModel) designed for application in any landscape and climate where snow is found. SnowTran-3D is typically run using temporal increments ranging from 1 hour to 1 day, horizontal grid increments ranging from 1 to 100 m and time-spans ranging from individual storms to entire snow seasons.

The temporal variability of surface snow and glacier melt flux and runoff are investigated for the ablation area of Jakobshavn Isbræ, West Greenland. High-resolution meteorological observations both on and outside the Greenland ice sheet were used as model input. SnowModel, a physically based spatially distributed meteorological and snow evolution modeling system, is used to simulate the temporal variability of Jakobshavn Isbræ accumulation and ablation processes for 2000/01–2006/07. Winter snow depth observations and MODIS satellite-derived summer melt observations are used for model validation of accumulation and ablation. The modeled interannual runoff variability varied from 1.81 × 109 m3 (2001/02) to 5.21 × 109 m3 (2004/05), yielding a cumulative runoff at the Jakobshavn Glacier terminus of ∼2.25 to ∼4.5 m w.e. The average modeled Jakobshavn runoff of ∼3.4 km3 a−1 was merged with previous estimates of Jakobshavn ice discharge to quantify the freshwater flux to Illulissat Icefjord. For both runoff and ice discharge the average trends are similar, indicating increasing (insignificant) influx of fresh water to Ilulissat Icefjord for the period 2000/01–2006/07. This study suggests that surface runoff forms a minor part of the overall Jakobshavn freshwater flux to the fjord: about 7% (∼3.4 km3 a−1) of the average annual freshwater flux of ∼51.0 km3 a−1 originates from the surface runoff.

We have mapped Antarctic blue-ice areas using the U.S. National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) Antarctica cloud-free image mosaic established by the United States Geological Survey. The mosaic consists of 38 scenes acquired from 1980 to 1994. Our results show that approximately 60 000 km2 of blue ice exist for each of the two main types of blue ice: “melt-induced” and “wind-induced”. Normally, the former type is located on slopes in coastal areas where climate conditions (i.e. persistent winds and temperature), together with favourable surface orientation, sustain conditions for surface and near surface melt. The latter blue-ice category occurs near mountains or on outlet glaciers, often at higher elevations, where persistent winds erode snow away year-round, and combined with sublimation creates areas of net ablation. Furthermore, we have identified an additional area of 121 000 km2 as having potential for blue ice. However, in these areas features such as mixed pixels, glazed snow surfaces, crevasses and/or shadows make interpretation more uncertain. In conclusion, a conservative estimate of Antarctic blue-ice area coverage by this method is found to be 120 000 km2 (∼0.8% of the Antarctic continent), with a potential maximum of 241 000 km2 (∼1.6% of the Antarctic continent).

Shallow lakes cover >25% of Alaska’s Arctic Coastal Plain. These remain frozen and snow-covered from October to June. The lake snow is thinner, denser, harder and has less water equivalent than snow on the surrounding tundra. Itcontains less depth hoar than land snow, yet paradoxically is subject to stronger temperature gradients. It also has fewer layers and these have been more strongly affected by wind. Dunes and drifts are better developedon lakes; they have wavelengths of 5–20 m, compared to <5 m on land. Because of these differences, lake snow has roughly half the thermal insulating capacity of land snow. The winter mass balance on lakes is also different because (1) some snow falls into the water before the lakes freeze, (2) some snow accumulates in drifts surrounding the lakes, and (3) prevailing winds lead to increased erosion and thinner snow on the eastern lake sides. Physical models that extrapolate land snow over lakes without appropriate adjustments for depth, density, distribution and thermal properties will under-predict ice thickness and winter heat losses.

Observed meteorological data and a high-resolution (5 km) model were used to simulate Greenland ice sheet surface melt extent and trends before the satellite era (1960–79) and during the satellite era through 2010°. The model output was compared with passive microwave satellite observations of melt extent. For 1960–2010 the average simulated melt extent was 15 ± 5%. For the period 1960–72, simulated melt extent decreased by an average of 6%, whereas 1973–2010 had an average increase of 13%, with record melt extent in 2010. The trend in simulated melt extent since 1972 indicated that the melt extent in 2010 averaged twice that in the early 1970s. The maximum and mean melt extents for 2010 were 52% (∼9.5 × 105 km2) and 28% (∼5.2 × 105 km2), respectively, due to higher-than-average winter and summer temperatures and lower-than-average winter precipitation. For 2010, the southwest Greenland melt duration was 41–60 days longer than the 1960–2010 average, while the northeast Greenland melt duration was up to 20 days shorter. From 1960 to 1972 the melting period (with a >10% melt extent) decreased by an average of 3 days a−1. After 1972, the period increased by an average of 2 days a−1, indicating an extended melting period for the ice sheet of about 70 days: 40 and 30 days in spring and autumn, respectively.

The McMurdo Dry Valleys, southern Victoria Land, East Antarctica, are a polar desert, and melt from glacial ice is the primary source of water to streams, lakes and associated ecosystems. Previous work found that to adequately model glacier ablation and subsurface ice temperatures with a surface energy-balance model required including the transmission of solar radiation into the ice. Here we investigate the contribution of subsurface melt to the mass balance of (and runoff from) Dry Valley glaciers by including a drainage process in the model and applying the model to three glacier sites using 13 years of hourly meteorological data. Model results for the smooth glacier surfaces common to many glaciers in the Dry Valleys showed that sublimation was typically the largest component of surface lowering, with rare episodes of surface melting, consistent with anecdotal field observations. Results also showed extensive internal melting 5–15 cm below the ice surface, the drainage of which accounted for ~50% of summer ablation. This is consistent with field observations of subsurface streams and formation of a weathering crust. We identify an annual cycle of weathering crust formation in summer and its removal during the 10 months of winter sublimation.

A physically based mathematical model of the coupled lake, lake ice, snow and atmosphere system is developed for studying terrestrial-atmospheric interactions in high-elevation and high-latitude regions. The ability to model lake-ice freeze-up, break-up, total ice thickness and ice type offers the potential to describe the effects of climate change in these regions. Model output is validated against lake-ice observations made during the winter of 1992–93 in Glacier National Park, Montana. U.S.A. The model is driven with observed daily atmospheric forcing of precipitation, wind speed and air temperature. In addition to simulating complete energy-balance components over the annual cycle, model output includes ice freeze-up and break-up dates, and the end-of-season clear ice, snow-ice and total ice depths for two nearby lakes in Glacier National Park, each in a different topographic setting. Modeled ice features are found to agree closely with the lake-ice observations.

Model simulations illustrate the key role that the wind component of the local climatic regime plays on the growth and decay of lake ice. The wind speed affects both the surface temperature and the accumulation of snow on the lake-ice surface. Higher snow accumulations on the lake ice depress the ice surface below the water line, causing the snow to become saturated and leading to the formation of snow-ice deposits. In regions having higher wind speeds, significantly less snow accumulates on the lake-ice surface, thus limiting snow-ice formation. The ice produced by these two different mechanisms has distinctly different optical and radiative properties, and affects the monitoring of frozen lakes using remote-sensing techniques.

As part of the winter environment in middle- and high-latitude regions, the interactions between wind, vegetation, topography and snowfall produce snow covers of non-uniform depth and snow water-equivalent distribution. A physically based numerical snow-transport model (SnowTran-3D) is developed and used to simulate this three-dimensional snow-depth evolution over topographically variable terrain. The mass-transport model includes processes related to vegetation snow-holding capacity, topographic modification of wind speeds, snow-cover shear strength, wind-induced surface-shear stress, snow transport resulting from saltation and suspension, snow accumulation and erosion, and sublimation of the blowing and drifting snow. The model simulates the cold-season evolution of snow-depth distribution when forced with inputs of vegetation type and topography, and atmospheric foreings of air temperature, humidity, wind speed and direction, and precipitation. Model outputs include the spatial and temporal evolution of snow depth resulting from variations in precipitation, saltation and suspension transport, and sublimation. Using 4 years of snow-depth distribution observations from the foothills north of the Brooks Range in Arctic Alaska, the model is found to simulate closely the observed snow-depth distribution patterns and the interannual variability.

In the Jutulgryta area of Dronning Maud Land, Antarctica, subsurface melting of the ice sheet has been observed. The melting takes place during the summer months in blue-ice areas under conditions of below-freezing air and surface temperatures. Adjacent snow-covered regions, having the same meteorological and climatic conditions, experience little or no subsurface melting. To help explain and understand the observed melt-rate differences in the blue-ice and snow-covered areas, a physically based numerical model of the coupled atmosphere, radiation, snow and blue-ice system has been developed. The model comprises a heat-transfer equation which includes a spectrally dependent solar-radiation source term. The penetration of radiation into the snow and blue ice depends on the solar-radiation spectrum, the surface albedo and the snow and blue-ice grain-sizes and densities. In addition, the model uses a complete surface energy balance to define the surface boundary conditions. It is run over the full annual cycle, simulating temperature profiles and melting and freezing quantities throughout the summer and winter seasons. The model is driven and validated using field observations collected during the Norwegian Antarctic Research Expedition (NARE) 1996–97. The simulations suggest that the observed differences between subsurface snow and blue-ice melting can be explained largely by radiative and heat-transfer interactions resulting from differences in albedo, grain-size and density between the two mediums.

To assess the response of lake Freeze-up and break-up dates to changes in atmospheric forcing, a physically based computational model of the coupled lake, lake-ice, snow and atmosphere system has been developed. Model performance is validated using meteorological and lake-ice observations from Great Slave Lake in northern Canada (1991/92) and St Mary Lake in Glacier National Park, Montana, (1992/93). Model integrations with modified atmospheric forcing indicate that air-temperature changes of ±4°C can delay or speed up the freeze-up and break-up dates by as much as 4 weeks for St Mary Lake, and 2 weeks for Great Slave Lake. For both lakes, break-up date is more sensitive to air-temperature changes than is freeze-up. Changes of ±3/10 cloud-cover fraction produce a shifting of break-tip dates by 1 week. Changes in wind speeds of ± 3 m s−1 modify the maximum ice depth of the lakes by 5–10 cm. For Great Slave Lake, lower wind speeds produced a surface temperature low enough to delay the onset of break-up by 2 weeks.

The McMurdo Dry Valleys of Antarctica host the coldest and driest ecosystem on Earth, which is acutely sensitive to the availability of water coming from glacial runoff. We modeled the spatial variability in ablation and assessed climate sensitivity of the glacier ablation zones using 16 years of meteorological and surface mass-balance observations collected in Taylor Valley. Sublimation was the primary form of mass loss over much of the ablation zones, except for near the termini where melt, primarily below the surface, dominated. Microclimates in ~10 m scale topographic basins generated melt rates up to ten times higher than over smooth glacier surfaces. In contrast, the vertical terminal cliffs on the glaciers can have higher or lower melt rates than the horizontal surfaces due to differences in incoming solar radiation. The model systematically underpredicted ablation for the final 5 years studied, possibly due to an increase of windblown sediment. Surface mass-balance sensitivity to temperature was ~−0.02 m w.e. K−1, which is among the smallest magnitudes observed globally. We also identified a high sensitivity to ice albedo, with a decrease of 0.02 having similar effects as a 1 K increase in temperature, and a complex sensitivity to wind speed.

Surface patterns of alternating snow and blue-ice bands are found in the Jutulgryta area of Dronning Maud Land, Antarctica. The snow-accumulation regions exist in the lee of blue-ice topographic ridges aligned perpendicular to winter winds. The snow bands are c. 500–2000 m wide and up to several kilometres long. In Jutulgryta, these features cover c. 5000 km2. These alternating snow and blue-ice bands are simulated using a snow transport and redistribution model, SnowTran-3D, that is driven with a winter cycle of observed daily screen-height air temperature, humidity, and wind speed and direction. The snow-transport model is coupled to a wind model that simulates wind flow over the relatively complex topography. Model results indicate that winter winds interact with the ice topographic features to produce alternating surface patterns of snow accumulation and erosion. In addition, model sensitivity simulations suggest that subtle topographic variations, on the order of 5m elevation change over a horizontal distance of 1 to 1.5 km, can lead to snow-accumulation variations that differ by a factor of six. This result is expected to have important consequences regarding the choice of sites for ice-coring efforts in Antarctica and elsewhere.

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